THRIVE, ASTRAL, and iScore scales for predicting prognosis of mechanical thrombectomy in patients with acute ischemic stroke.

OBJECTIVE: To validate the predictive performance of the THRIVE, ASTRAL, and iScore scales for clinical functional outcomes following mechanical thrombectomy (MT) for acute ischemic stroke (AIS). METHODS: A total of 111 patients meeting the inclusion criteria were included in this study, with 59 (53.2%) having a good prognosis and 52 (46.8%) having a poor prognosis. MedCalc software was applied to plot receiver operating characteristic (ROC) curves, calculate the area under the curve (AUC), and compare the predictive efficacy of the three scales two by two using Delong text. Statistical significance was defined as Pc < 0.05. RESULTS: Logistic binary regression multifactorial analysis revealed that iScore is one of the poor predictors of prognosis in patients with MT. The AUC values for the THRIVE, ASTRAL, and iScore scales in predicting prognosis after MT were found to be 0.713, 0.738, and 0.820, respectively. CONCLUSION: The iScore is a reliable tool for assessing the poor prognosis of MT in patients with AIS.

Relationship between maximum carotid plaque area and prognosis of patients with acute ischaemic stroke.

OBJECTIVE: In this study, the relationship between maximum carotid plaque area and stroke prognosis was analysed by carotid ultrasonography, and the relevant risk factors affecting the prognosis of acute ischaemic stroke (AIS) were investigated to provide novel insights into stroke prevention and management. METHODS: A total of 205 AIS patients with carotid plaques were included in this study. Based on the mRS score at discharge, patients with AIS were classified into the good prognosis group (mRS ≤ 2) and poor prognosis group (mRS ≥ 3). SPSS 25.0 was used to analyse the data. Univariate and multivariate analyses were performed on the two groups with good and poor prognosis. Comparison between good and poor prognosis in patients with AIS in different circulatory systems was performed using the Kruskal-Wallis test. Differences were considered statistically significant at P < 0.05. RESULTS: Comparison of baseline data revealed differences in carotid plaque diameter, carotid intima-media thickness, maximum carotid plaque area, history of previous stroke and plaque echogenicity between the good and poor prognosis groups (P < 0.05). Results of multifactorial analyses of logistic binary regression indicated that history of previous stroke and maximum carotid plaque area were predictors of poor prognosis, with odds ratio of 2.515 (95%CI [1.327-4.764]) and 1.019 (95%CI [1.006-1.032]), respectively. CONCLUSION: The maximum carotid plaque area and history of previous stroke are important predictors for assessing prognosis in patients with AIS.